Health expenditure and gross domestic product: causality analysis by income level
The empirical findings on the relationship between gross domestic product (GDP) and health expenditure are diverse. The influence of income levels on this causal relationship is unclear. This study examines if the direction of causality and income elasticity of health expenditure varies with income level. It uses the 1995–2014 panel data of 161 countries divided into four income groups. Unit root, cointegration and causality tests were employed to examine the relationship between GDP and health expenditure. Impulse-response functions and forecast-error variance decomposition tests were conducted to measure the responsiveness of health expenditure to changes in GDP. Finally, the common correlated effects mean group method was used to examine the income elasticity of health expenditure. Findings show that no long-term cointegration exists, and the growth in health expenditure and GDP across income levels has a different causal relationship when cross-sectional dependence in the panel is accounted for. About 43% of the variation in global health expenditure growth can be explained by economic growth. Income shocks affect health expenditure of high-income countries more than lower-income countries. Lastly, the income elasticity of health expenditure is less than one for all income levels. Therefore, healthcare is a necessity. In comparison with markets, governments have greater obligation to provide essential health care services. Such results have noticeable policy implications, especially for low-income countries where GDP growth does not cause increased health expenditure.
KeywordsHealth expenditure Gross domestic product Westerlund cointergration Causality analysis Impulse response function Common correlated effects
JEL ClassificationC55 I10 I15 O1
The paper was part of the first author’s Ph.D. study. The Ph.D. program was financed by the University of Southern Queensland, Australia [USQ International Stipend Research Scholarship and USQ International Fees Research Scholarship].
Compliance with ethical standards
Conflict of interest
The authors declare no conflict of interest.
- Atilgan, E., Kilic, D., & Ertugrul, H. M. (2016). The dynamic relationship between health expenditure and economic growth: Is the health-led growth hypothesis valid for Turkey? European Journal of Health Economics,18(5), 567–574. https://doi.org/10.1007/s10198-016-0810-5.PubMedCrossRefGoogle Scholar
- Ke, X., Saksena, P., & Holly, A. (2011). The determinants of health expenditure: A country-level panel data analysis. Working paper of the Results for Development Institute (R4D). Geneva: World Health Organization. www.resultsfordevelopment.org. Accessed on August 11th, 2017.
- Mladenović, I., Milovančević, M., Sokolov Mladenović, S., Marjanović, V., & Petković, B. (2016). Analyzing and management of health care expenditure and gross domestic product (GDP) growth rate by adaptive neuro-fuzzy technique. Computers in Human Behavior,64, 524–530. https://doi.org/10.1016/j.chb.2016.07.052.CrossRefGoogle Scholar
- Pesaran, M. H. (2004). General diagnostic tests for cross section dependence in panels. CESifo GmbH, CESifo working paper series: CESifo Working Paper No. 1229. http://ezproxy.usq.edu.au/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=ecn&AN=0906171&site=ehost-live. http://www.cesifo.de/DocCIDL/1229.pdf. Accessed January 14th, 2018.
- van der Gaag, J., & Stimac, V. (2008). Towards a new paradigm for health sector development. Amsterdam: Amsterdam Institute for International Development. https://www.r4d.org/wpcontent/uploads/Toward-a-New-Paradigm-for-Health-Sector-Development.pdf. Accessed on November 7th, 2017.
- Wooldridge, J. (2002). Econometric analysis of cross section and panel data. Cambridge: MA: MIT Press.Google Scholar
- World Bank. (2016). World development indicators. http://databank.worldbank.org/data/reports.aspx?source=world-development-indicators. Accessed on May 21st, 2017.
- World Health Organization. (2016). Global health observatory data repository. http://apps.who.int/gho/data/view.main.healthexpratioglobaL?lang=en. Accessed on May 21st, 2017.